利用限制隨機賽局在認知網路下動態管理功率

Abstract

近年研究指出,已分配頻帶的頻寬使用效率低，而為了促使頻寬使用效率的提升，認知網路(Cognitive Radio, CR)則被提出來動態的使用這些已分配卻效率不高的頻帶。其中在認知網路中使用者之間的訊號干擾與功率分配則被提出許多的相關研究。因此，在這篇論文中,使用賽局理論(Game Theory)的限制隨機賽局(Constrianed Stochastic Game)在動態的通道環境與存在頻寬的使用者下，求出此問題的最佳決策。內容的研究中，分別求出有限時間和無限時間下，包含了已分配與未分配頻帶的最佳決策。而在求解的過程中，均對信號的干擾做了限制，因此CR的使用者對頻寬的擁有者不會造成嚴重的干擾。根據賽局理論模型的表示，可以證明存在賽局的奈許平衡解(Nash equilibrium)，而此奈許平衡解可以使每個CR使用者在彼此競爭的情況下得到個人的最佳化。在模擬的部分，驗證了確實可達到奈許平衡解，也顯示可優於貪婪式的演算法(Greedy mechanism)，並且對有通道感測的誤差下仍可達到可預期的結果。

Recent studies have been conducted to indicate the ineffective usage of licensed bands due to the static spectrum allocation. In order to improve the spectrum utilization, the cognitive radio is therefore suggested to dynamically exploit the opportunistic primary frequency spectrums. The interference from the secondary users to the primary user consequently draws the attention to the spectrum and power management for the cognitive radio networks. In this paper, the constrained stochastic games are utilized to exploit the optimal policies for power management by considering the variations from both the channel gain and the primary traffic. Both the underlay and overlay waveforms are considered within the network scenarios for the proposed power management scheme. Constraints for allowable interferences will be applied in order to preserve the communication quality among the primary and the secondary users. With the assumption of the Markovian property of dynamic environment, finite and infinite time horizon scenarios are both considered in target function. According to the formulation of the constrained stochastic games, the existence of the constrained Nash equilibrium will be validated with rigorous proofs. Simulation results further validate the correctness of the theoretically-derived policies, compare with the greedy mechanism and examine the effect of channel sensing error for dynamic power management.